Search Results - (( normal distribution methods algorithm ) OR ( data distribution function algorithm ))

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  1. 1

    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

    Published 2015
    “…Anderson-Darling (AD) and Goodness of Fit test is used to identify the best fitted distribution model to the real data. Four traffic distribution which are normal, lognormal, Weibull and exponential distribution are fitted and derived. …”
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    Article
  2. 2

    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

    Published 2015
    “…Anderson-Darling (AD) and Goodness of Fit test is used to identify the best fitted distribution model to the real data. Four traffic distribution which are normal, lognormal, Weibull and exponential distribution are fitted and derived. …”
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    Thesis
  3. 3

    Robust Kernel Density Function Estimation by Dadkhah, Kourosh

    Published 2010
    “…The distance of observations from the center of data set is incorporated in the formulation of the first outlier detection method in unimodal distribution. …”
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    Thesis
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  5. 5

    A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

    Published 2020
    “…The obtained results were compared with the BH and previous optimization algorithms for both test functions as well as data clustering in terms of normal and high dimensional datasets. …”
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    Thesis
  6. 6

    PSO modelling and PID controlled of automatic fish feeder system by W Mahmud, Wan Muhammad Azlan

    Published 2020
    “…The main objective of this study is to improve the performance of fish feeding system by using PID controller through ARX modelling. In this study, raw data at distribution part with speed of 130 rpm, 160 rpm, 190 rpm, 220 rpm and 250 rpm were extracted and used to determine ARX equation parameters as transfer function by using PSO algorithm to optimize ARX model parameter. …”
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    Thesis
  7. 7

    Fault identification in pipeline system using normalized hilbert huang transform and automatic selection of intrinsic mode function by Hanafi, M. Yusop, M. F., Ghazali, M. F. M., Yusof, M. A., Pi Remli

    Published 2018
    “…The analysis results using Normalized Ikaz proven that the method can be apply as an automatic selection of intrinsic mode function (IMF) although the noise level ratio of the signal is lower. …”
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    Conference or Workshop Item
  8. 8

    Transient analysis for leak signature identification based on Hilbert Huang transform and integrated kurtosis algorithm for z-notch filter technique by Muhammad Hanafi, Yusop

    Published 2018
    “…However, this method has the difficulty in selecting the suitable IMF for the next data post-processing method, which is Hilbert Transform (HT). …”
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    Thesis
  9. 9

    Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

    Published 2014
    “…The direct idea of making the conventional neural network learning algorithm more powerful towards outlying data is by replacing the mean square error (MSE) with a different symmetric and continuous cost function. …”
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    Book Section
  10. 10

    Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques by Googhari, Shahram Karimi

    Published 2007
    “…The reservoir inflow and rainfall data sets were examined for normal distribution and the best data transformation was used. …”
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    Thesis
  11. 11

    Clustering autism spectrum disorder student’s system based on intelligence, skills and behavior using agglomerative clustering algortihm / Daarin Nadia Nordin by Nordin, Daarin Nadia

    Published 2020
    “…Data cleaning and data transformation is first carried out, followed by normalization through the Z-score method before being processed in the clustering model. …”
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    Thesis
  12. 12

    Enhancing clustering algorithm with initial centroids in tool wear region recognition by Kasim, Nur Adilla, Nuawi, Mohd Zaki, Abdul Ghani, Jaharah, Ngatiman, Nor Azazi, Che Haron, Che Hassan, Muhammad Rizal

    Published 2020
    “…Autonomous manufacturing allows the system to distinguish between a mild, normal and total failure in tool condition. K-means clustering has become the most applied algorithm in discovering classes in an unsupervised scenario. …”
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    Article
  13. 13

    Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

    Published 2015
    “…These results indi�cate that the proposed method can improve the RAN learning algorithm towards the large-scale stream data processing. …”
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    Thesis
  14. 14

    Improved performance in distributed estimation by convex combination of DNSAF and DNLMS algorithms by Ahmad Pouradabi, Amir Rastegarnia, Azam Khalili, Ali Farzamnia

    Published 2022
    “…Diffusion normalized least mean square (DNLMS) algorithm has low misadjustment error, but it is slow in convergence. …”
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    Proceedings
  15. 15

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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    Thesis
  16. 16

    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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    Monograph
  17. 17

    Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan by Hassan, Siti Fatimah

    Published 2015
    “…For example, the distribution analogues to the normal distribution in linear data is known as circular normal distribution. …”
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    Thesis
  18. 18

    Statistical approach on grading: mixture modeling by Md. Desa, Zairul Nor Deana

    Published 2006
    “…Statistical approaches which use the Standard Deviation and conditional Bayesian methods are considered to assign the grades. In the conditional Bayesian model, we assume the data to follow the Normal Mixture distribution where the grades are distinctively separated by the parameters: means and proportions of the Normal Mixture distribution. …”
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    Thesis
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